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Purpose

Enables Life Scientists to Understand the Purpose and Uses of Classical Statistics as an Integral Part of the Scientific Method

 

Topics Covered:

  • Good experimental design and sources of bias.
  • Systematic versus random error.
  • The distinction between samples and populations.
  • The most appropriate ways to describe samples.
  • Estimation and the principle of hypothesis testing.
  • The Standard Error of the Mean and confidence intervals.
  • Understanding and reporting uncertainty.
  • Power, Type I and type II errors.
  • Standard parametric tests and their interpretations, including p-values, test statistics and associated distributuions.

Our Teaching Approach:

  • Emphasises hands-on learning using custom interactive web apps that demonstrate statistical concepts in real-time.
  • Uses in-class exercises and quizzes to reinforce student understanding.
  • Implements a single story-line throughout the workshop allowing students to see how statistics is involved at every step of the scientific method

Science Craft’s Distinctive Advantage:

  • A reference book written for the specific needs of life scientists who have little or no experience with using and understanding statistics.
  • Workshop material developed in collaboration with a statistician currently active in research.
  • Interactive web apps and video animations developed specifically for the workshop complement specific topics in the workshop.

The t distribution, another key distribution in classical statistics, is discussed in context.
Course Details
Duration: 2-3 full days
Maximum Capacity: 12 participants with one (or two) instructor(s)
Instructors: Dr. Rick Scavetta and/or Dr. Irina Czogiel

Feedback

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Nice overview, really liked it… I think I need more of this.

I got a good introduction and understanding about statistics.

Contents were very well-explained, good examples, good visualistions.

Good overall introductory course for people with only minor knowledge.

Good overview of many topics in statistics.

  Workshop Description   Table of Contents  

 

 


Concepts in linear regression are explained with simple and easy-to-understand examples and visuals.